2018 Sep Opinions
All (106) | Courses, Education (5) | Meetings (12) | News, Features (13) | Opinions (28) | Top Stories, Tweets (9) | Tutorials, Overviews (29) | Webcasts & Webinars (10)
- Learning mathematics of Machine Learning: bridging the gap - Sep 28, 2018.
We outline the four key areas of Maths in Machine Learning and begin to answer the question: how can we start with high school maths and use that knowledge to bridge the gap with maths for AI and Machine Learning?
- ODSC India Highlights: Deep Learning Revolution in Speech, AI Engineer vs Data Scientist, and Reinforcement Learning for Enterprise - Sep 26, 2018.
Key takeaways and highlights from ODSC India 2018 conference about the latest trends, breakthroughs and revolutions in the field of Data Science and Artificial Intelligence
- What If the Data Tells You to Be Racist? When Algorithms Explicitly Penalize - Sep 26, 2018.
Without the right precautions, machine learning — the technology that drives risk-assessment in law enforcement, as well as hiring and loan decisions — explicitly penalizes underprivileged groups.
- Datmo: the Open Source tool for tracking and reproducible Machine Learning experiments - Sep 26, 2018.
As a data scientist, managing environments and experiments is always hard and results in wasted time and effort with all the troubleshooting and lost work. With datmo, you can track your experiments using this common standard and not worry about reproduction of previous work.
- When Bayes, Ockham, and Shannon come together to define machine learning - Sep 25, 2018.
A beautiful idea, which binds together concepts from statistics, information theory, and philosophy.
- Building a Machine Learning Model through Trial and Error - Sep 24, 2018.
A step-by-step guide that includes suggestions on how to preprocess data and deriving features from this. This article also contains links to help you explore additional resources about machine learning methods and other examples.
- Diversity in Data Science: Overview and Strategy - Sep 24, 2018.
We take a hard look at diversity within the tech industry, root causes, and potential solutions and highlight resources/initiatives that can connect readers with programs aiding their professional development.
- Cartoon: Where AI achieves excellence - Sep 22, 2018.
We examine what can happen when lawyers are replaced with Machine Learning.
- Data Capture – the Deep Learning Way - Sep 21, 2018.
An overview of how an information extraction pipeline built from scratch on top of deep learning inspired by computer vision can shakeup the established field of OCR and data capture.
- A Deep (But Jargon Free) Dive Into Deep Learning - Sep 20, 2018.
Learn what exactly deep learning is, how it works, and about its growing and innovative applications in healthcare, finance, retail, and more with this illustrated guide.
- Customer Data Unicorns: Why how we manage their data is the secret to finding, taming and riding them - Sep 20, 2018.
The process of how we listen, think, talk and do using this data is not possible without the effective management thereof. This skill enables the business to exploit this asset and ride these Majestic Unicorns.
- Deep Learning on the Edge - Sep 19, 2018.
Detailed analysis into utilizing deep learning on the edge, covering both advantages and disadvantages and comparing this against more traditional cloud computing methods.
- How many data scientists are there and is there a shortage? - Sep 18, 2018.
We examine the famous McKinsey prediction from 2011 and look into whether there a shortage of people with analytical expertise and estimate how many Data Scientists are there.
- Free resources to learn Natural Language Processing - Sep 18, 2018.
An extensive list of free resources to help you learn Natural Language Processing, including explanations on Text Classification, Sequence Labeling, Machine Translation and more.
- A Winning Game Plan For Building Your Data Science Team - Sep 18, 2018.
We need to understand the responsibilities, capabilities, expectations and competencies of the Data Engineer, Data Scientist and Business Stakeholder.
- 10 Big Data Trends You Should Know - Sep 17, 2018.
A collection of Big Data trends to familiarize yourself with, covering IoT Networks, Artificial Intelligence, Predictive Analytics, Dark Data and more.
- You Aren’t So Smart: Cognitive Biases are Making Sure of It - Sep 17, 2018.
Cognitive biases are tendencies to think in certain ways that can lead to systematic deviations from a standard of rationality or good judgment. They have all sorts of practical impacts on our lives, whether we want to admit it or not.
- Ethics + Data Science: opinion by DJ Patil, former US Chief Data Scientist - Sep 14, 2018.
How much has data changed our lives over the past decade? Former US Chief Data Scientist DJ Patil investigates.
- The Growing Participation of Women in the Data Science Community - Sep 14, 2018.
We still have a long way to go before the gender representation becomes more equalized, but the field at large indicates hopeful trends about women working in the role or desiring to do so in the future.
- The Data Science of “Someone Like You” or Sentiment Analysis of Adele’s Songs - Sep 13, 2018.
An extensive analysis of Adele's songs using Natural Language Processing (NLP) on the lyrics, to uncover the underlying emotions and sentiments.
- The Economics and Benefits of Artificial Intelligence - Sep 13, 2018.
In this article, focus on current AI, which is mostly based on the algorithms that can do predictions, and discuss how the economics of AI works and how it may affect business.
- Hadoop for Beginners - Sep 12, 2018.
An introduction to Hadoop, a framework that enables you to store and process large data sets in parallel and distributed fashion.
- Key Takeaways from KDD 2018: a Deconfounder, Machine Learning at Pinterest, Knowledge Graph - Sep 11, 2018.
Highlights and key takeaways from KDD 2018, 24th ACM SIGKDD conference on Data Science and Data Mining: including what is a deconfounder, how Pinterest approaches Machine Learning, Knowledge Graph for Products, and Differential Privacy.
- Journey to Machine Learning – 100 Days of ML Code - Sep 7, 2018.
A personal account from Machine Learning enthusiast Avik Jain on his experiences of #100DaysOfMLCode, a challenge that encourages beginners to code and study machine learning for at least an hour, every day for 100 days.
- Don’t Use Dropout in Convolutional Networks, by Harrison Jansma - Sep 5, 2018.
If you are wondering how to implement dropout, here is your answer - including an explanation on when to use dropout, an implementation example with Keras, batch normalization, and more.
- What on earth is data science? - Sep 4, 2018.
An overview and discussion around data science, covering the history behind the term, data mining, statistical inference, machine learning, data engineering and more.
- 5 Resources to Inspire Your Next Data Science Project - Sep 4, 2018.
In this post, my intention is provide some useful tips and resources to springboard you into your next data science project.
- Cartoon: Labor Day in the year 2050 - Sep 2, 2018.
KDnuggets cartoon looks at how Labor Day can change in the year 2050.